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## ex5_4_3.gms:

#### References:

• Floudas, C A, Pardalos, P M, Adjiman, C S, Esposito, W R, Gumus, Z H, Harding, S T, Klepeis, J L, Meyer, C A, and Schweiger, C A, Handbook of Test Problems in Local and Global Optimization. Kluwer Academic Publishers, 1999.
• Visweswaran, V, and Floudas, C A, Computational Results for an Efficient Implementation of the GOP Algorithm and its Variants. In Grossmann, I E, Ed, Global Optimization in Engineering Design. Kluwer Books, 1996.
• Original source: Global Model of Chapter 5 ex5.4.3.gms from Floudas e.a. Test Problems

Point: p1
Best known point: p1 with value 4845.4620

* NLP written by GAMS Convert at 07/19/01 13:39:40 * * Equation counts * Total E G L N X * 14 14 0 0 0 0 * * Variable counts * x b i s1s s2s sc si * Total cont binary integer sos1 sos2 scont sint * 17 17 0 0 0 0 0 0 * FX 0 0 0 0 0 0 0 0 * * Nonzero counts * Total const NL DLL * 43 25 18 0 * * Solve m using NLP minimizing objvar; Variables x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,x11,x12,x13,x14,x15,x16,objvar; Positive Variables x5,x6,x7,x8,x9,x10,x11,x12; Equations e1,e2,e3,e4,e5,e6,e7,e8,e9,e10,e11,e12,e13,e14; e1.. x5 + x9 =E= 10; e2.. x5 - x6 + x11 =E= 0; e3.. x7 + x9 - x10 =E= 0; e4.. - x6 + x7 + x8 =E= 0; e5.. - x10 + x11 + x12 =E= 0; e6.. x16*x11 - x13*x6 + 150*x5 =E= 0; e7.. x15*x7 - x14*x10 + 150*x9 =E= 0; e8.. x6*x15 - x6*x13 =E= 1000; e9.. x10*x16 - x10*x14 =E= 600; e10.. x1 + x15 =E= 500; e11.. x2 + x13 =E= 250; e12.. x3 + x16 =E= 350; e13.. x4 + x14 =E= 200; e14.. - (1300*(1000/(0.0333333333333333*x1*x2 + 0.166666666666667*x1 + 0.166666666666667*x2))**0.6 + 1300*(600/(0.0333333333333333*x3*x4 + 0.166666666666667*x3 + 0.166666666666667*x4))**0.6) + objvar =E= 0; * set non default bounds x1.lo = 10; x1.up = 350; x2.lo = 10; x2.up = 350; x3.lo = 10; x3.up = 200; x4.lo = 10; x4.up = 200; x5.up = 10; x6.up = 10; x7.up = 10; x8.up = 10; x9.up = 10; x10.up = 10; x11.up = 10; x12.up = 10; x13.lo = 150; x13.up = 310; x14.lo = 150; x14.up = 310; x15.lo = 150; x15.up = 310; x16.lo = 150; x16.up = 310; * set non default levels * set non default marginals Model m / all /; m.limrow=0; m.limcol=0; \$if NOT '%gams.u1%' == '' \$include '%gams.u1%' Solve m using NLP minimizing objvar;